Pursuing high catalytic selectivity is challenging but paramount for an efficient and low-cost CO2 electrochemical reduction (CO2R). In this work, we demonstrate a significant correlation between the selectivity of CO2R to formate and the duration of tin (Sn) electrodeposition over a cuprous oxide (Cu2O)-derived substrate. A Sn electrodeposition time of 120 s led to a cathode with a formate Faradaic efficiency of around 81% at −1.1 V vs reversible hydrogen electrode (RHE), which was more than 37% higher than those of the Sn foil and the sample treated for 684 s. This result highlights the significant role of the interface between deposited Sn and the cuprous-derived substrate in determining the selectivity of CO2R. High-resolution X-ray photoelectron spectra revealed that the residual cuprous species at the Cu/Sn interfaces could stabilize Sn species in oxidation states of 2+ and 4+, a mixture of which is essential for a selective formate conversion. Such modulation effects likely arise from the moderate electronegativity of the cuprous species that is lower than that of Sn2+ but higher than that of Sn4+. Our work highlights the significant role of the substrate in the selectivity of the deposited catalyst and provides a new avenue to advance selective electrodes for CO2 electrochemical reduction.
Easy and rapid analyte detection can be democratised using fabric-based colorimetric sensor, which can be readily incorporated into everyday clothing or accessories, and digitally imaged by non-expert users using pervasive smartphones. However, fabricating colorimetric arrays, particularly enzyme-based sensors, on fabrics is nontrivial because enzyme activity cannot be guaranteed upon solid-state immobilisation on textiles, and because textiles present a highly-textured surface that could cause interference during digital imaging and reduce the limit of detection of known sensing formulations. Here, an enzyme-based multilayer sensor is fabricated on selected fabrics via physical adsorption and drop-casting, and utilised for proof-of-concept colorimetric detection of glucose on textiles. Substrates like cotton, cotton lycra, and filter paper are compared for colour uniformity and potential interference during digital imaging. Colour development on cotton achieved optimal homogeneity and reproducibility. The entrapment of enzymes with polyvinyl alcohol is demonstrated to enhance linear dynamic range, water fastness, and storage stability under different conditions. An image-processing algorithm is developed in OpenCV to automatically detect the colour spot and aid in quantitative analysis of glucose concentration. The present study suggests a facile strategy to fabricate a robust biosensor on textile that can achieve noninvasive monitoring of glucose in human biological fluid.
Humans use textiles to maintain thermal homeostasis amidst environmental extremes but known textiles have limited thermal windows. There is evidence that polar-dwelling animals have evolved a different mechanism of thermoregulation by using optical polymer materials to achieve an on-body “greenhouse” effect. Here, we design a bilayer textile to mimic these adaptations. Two ultralightweight fabrics with complementary optical functions, a polypropylene visible-transparent insulator and a nylon visible-absorber–infrared-reflector coated with a conjugated polymer, perform the same putative function as polar bear hair and skin, respectively. While retaining familiar textile qualities, these layers suppress dissipation of body heat and maximize radiative absorption of visible light. Under moderate illumination of 130 W/m2, the textile achieves a heating effect of +10 °C relative to a typical cotton T-shirt which is 30% heavier. Current approaches to personal radiative heating are limited to absorber/reflector layer optimization alone and fail to reproduce the thermoregulation afforded by the absorber–transmitter structure of polar animal pelts. With increasing pressures to adapt to a rapidly changing climate, our work leverages optical polymers to bridge this gap and evolve the basic function of textiles.
Colorimetric analysis of biomarkers in biological fluids, such as sweat and saliva, using textile- and paper-based platforms promises to be a powerful point-of-care analytical tool. Despite exponential advances in material design, device fabrication and image processing over the past years, the majority of paper/fabric-based analytical strips and devices, thus far, are strictly restricted to controlled laboratory settings. In situ and real time monitoring of biological analytes using familiar garments or accessories are centered around electrochemical sensors. In contrast, colorimetric devices that can theoretically enable the quantification of analyte concentration when coupled with image capture devices (such as a smartphone cameras) are comparatively fewer and less advanced. Here, garment design strategies and various embodiments of wireless communication electronics are applied cooperatively to afford a noninvasive platform for quantitative monitoring of a test-bed biomarker, glucose. The electronics-embedded garments contain two functional parts: a functionalized cotton substrate with enzyme/chromogenic reagent and a near-field communication device. The enzyme/chromogenic reagent mixture is directed into a circular reservoir created on the cotton substrate via the capillary force of the cotton and hydrophobic wax barrier created via a cheap and simple wax-drawing technique. This wax barrier limits the irregular flow of the reagent mixture. The second part is a near-field-communication system that causes no irritation and discomfort to the skin. Once a smartphone is put at a close distance, the electronic system can enable the wireless transmission. A built-in application was developed to automatically detect the sensor spot via a signal processing pipeline and extract the R, G and B channel intensities for database construction and analysis. The chemical properties and geometric structures of the glucose sensor were optimized with the aid of a combinatorial method—materials optimization and mathematical optimization. The former aims to overcome the blurring and the loss of the signal due to enzyme washout from the detection zone under capillary forces exerted during wear. This problem was mitigated by immobilizing the enzyme inside a chitosan-carboxymethyl cellulose hybrid via a precisely controlled layer-by-layer deposition protocol. The sensor was further characterized by field-emission scanning electron microscopy (FESEM) to understand long term storage stability and surface morphology-dependent colorimetric response. A mathematical strategy was utilized for the design and selection of an optimal near-field measurement system. This optimization procedure is particularly important for commercialization. It aims to minimize the number of experiments and reduce the quantity of the chromogenic reagent mixture that needs to be deposited on the cotton substrate. Central composite designs were used to estimate the effect of individual variables (i.e. glucose oxidase concentration, horseradish peroxidase concentration and 3,3’,5,5’-Tetramethylbenzidine concentration) and their interactions on the optimization of the color intensity. The significance of the main and interaction effects and the applicability of the model were inferred from the analysis of variance (ANOVA). The optimum value was verified and validated with experimental results. This textile-based colorimetric sensing platform exhibits simple-to-fabricate, and cost-effective nature which might facilitate the broad commercial usage in health monitoring and clinical diagnosis.
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